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100 results for "neuroimaging" · page 6 of 10 · ranked by relevance

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on005777
Electrical_Morphine_Placebo_2018

NIRS

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005777-blue…

Participants

14

Size

864 MB

Version

vv1.0.0

Updated

Jul 10, 2026

by Peng et al. OpenNeuro ds005777
on004022
Multimodal EEG and fNIRS Biosignal Acquisition during Motor Imagery Tasks in Patients with Orthopedic Impairment

EEG

Imported from OpenNeuro ds004022

Participants

7

Channels

18

Citations

2

Size

635 MB

Version

vv1.0.0

Updated

Jul 10, 2026

by Seho Lee et al. OpenNeuro ds004022
on007719
Cambridge_data_resting

NIRS

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on007719-blue…

Participants

65

Size

8.62 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Enter author names here OpenNeuro ds007719
nm000177
Multi-session longitudinal motor imagery EEG dataset (Kumar et al. 2024)

EEG

A longitudinal motor imagery EEG dataset from 18 brain-computer interface (BCI)-naive subjects acquired across 6 sessions (1 offline + 5 online) to investigate transfer learning and domain adaptation for calibration-free BCI training. Subjects performed left/right hand motor imagery tasks with visual feedback using 22 EEG channels sampled at 512 Hz. The dataset compares Generic Recentering (unsupervised) and Personally Assisted Recentering (supervised) domain adaptation frameworks, with features extracted as covariance matrices and classified using Riemannian geometry-based methods.

Participants

18

Channels

22 (10-10)

HED

v8.4.0

Size

1.66 GB

Version

vv1.0.1

Updated

Jul 10, 2026

by Satyam Kumar et al.
on004851
HID

EEG

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004851-blue…

Participants

66

Channels

72 (10-10)

Size

56.6 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Tony Johnson et al. OpenNeuro ds004851
nm000242
Visual imagery EEG dataset from Gao et al 2026

EEG

A 32-channel EEG dataset comprising visual imagery recordings from 22 healthy participants performing mental imagery tasks of 10 distinct categories (animals, geometric figures, and objects). The dataset contains 16,800 trials collected across 2 sessions per subject with simultaneous EEG acquisition at 1000 Hz, designed to support brain-computer interface research and classification algorithm development.

Participants

22

Citations

1

HED

v8.4.0

Size

31.7 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Jing'ao Gao et al.
on005007
Auditory naming task with questions that begin or end with a wh-interrogative

iEEG

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005007-blue…

Participants

40

Size

7.99 GB

Version

vv1.0.0

Updated

Jul 10, 2026

by Yu Kitazawa et al. OpenNeuro ds005007
nm000178
BNCI 2020-001 Reach-and-Grasp Electrode Comparison EEG dataset

EEG

This dataset comprises EEG recordings from 15 healthy participants performing self-initiated reach-and-grasp motor tasks using three different recording systems: gel-based laboratory equipment, water-based mobile EEG, and dry-electrode mobile EEG. Data were acquired at 256 Hz from 58 EEG channels plus 6 EOG channels across three sessions with a total of 7,200 trials. Participants executed palmar and lateral grasp actions toward objects while EEG signals were recorded. The study investigates the feasibility of decoding natural reach-and-grasp neural correlates across different EEG acquisition modalities for brain-computer interface applications.

Participants

45

Channels

58 (10-05)

HED

v8.4.0

Size

2.08 GB

Version

vv1.0.1

Updated

Jul 10, 2026

by Andreas Schwarz et al.
on005929
Motion-Yucel2014

NIRS

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005929-blue…

Participants

7

Size

68.5 MB

Version

vv1.0.0

Updated

Jul 10, 2026

by Yücel et al. OpenNeuro ds005929
nm000274
BEETL Competition 2021 Motor Imagery Dataset B — transfer learning benchmark

EEG

Beetl2021-B is a preprocessed 32-channel EEG dataset from the NeurIPS 2021 BEETL competition designed for benchmarking transfer learning and domain adaptation algorithms in motor imagery brain-computer interfaces. The dataset comprises EEG recordings from 2 healthy subjects performing 4-class motor imagery tasks (left hand, right hand, feet, and rest) sampled at 200 Hz, with 1590 total trials organized for cross-subject and cross-dataset generalization assessment.

Participants

2

Channels

32 (10-10)

HED

v8.4.0

Size

31.3 MB

Updated

Jul 10, 2026

by Xiaoxi Wei et al.